U.S. Pat. No. 4,809,222: Associative and Organic Memory and Methods. Filed Jun. 20, 1986, Issued Feb. 28, 1989.
U.S. Pat. No. 4,984,176: The VDH Biocomputer. Filed Jan. 11, 1988, Issued Jan. 8, 1991.
U.S. Pat. No. 5,375,250: Method of Intelligent Computing and Neural-Like Processing of Time and Space Functions. Filed Jul. 13, 1992, Issued Dec. 20, 1994.
U.S. Pat. No. 5,503,161: Universal Medical Instrument Based on Spectrum Analysis. Filed Oct. 25, 1993, Issued Apr. 2, 1996.
U.S. Pat. No. 4,809,222: Associative and Organic Memory and Methods, filed Jun. 20, 1986 and issued Feb. 28, 1989 documents an exploration of xe2x80x9cintelligencexe2x80x9d in computers. One of the references cited was an article entitled xe2x80x9cNeural Networks are Naive, Says Minsky.xe2x80x9d In 1986 the experts were pondering the potential of neurocomputing and the meaning of the word xe2x80x9cintelligence.xe2x80x9d The invention""s contribution was a xe2x80x9cmemory that can forget.xe2x80x9d This led to a neural network with surprising abilities, for instance changing priorities and real-time frequency spectrum analysis without the painful computations and memory requirements. Even though the proposed embodiment used analog circuits, the claims allowed for the use of digital circuitsxe2x80x94for instance multipliersxe2x80x94xe2x80x9cwhen they become availablexe2x80x9d.
U.S. Pat. No. 4,984,176: The VDH Biocomputer, filed Jan. 11, 1988 and issued Jan. 8, 1991, further explored the requirements of a computer for xe2x80x9cintelligence.xe2x80x9d The issue of software was also explored. The main idea was to minimize the added hardware and software complexity when the scale and scope of the applications increase.
U.S. Pat. No. 5,375,250: Method of Intelligent Computing and Neural-Like Processing of Time and Space Functions, filed Jul. 13, 1992 and issued Dec. 20, 1994, redefines the hardware used in the previous patent and further elaborates on the functions that can be performed in real time by the neural network first introduced in U.S. Pat. No. 4,809,222 (Associative and Organic Memory and Methods.) Algorithmsxe2x80x94heuristic searches, back propagation of errors, etc.xe2x80x94that are used in more conventional neural networks apply but were not elaborated on. In this patent the neural engine was renamed xe2x80x9cResonant Processor.xe2x80x9d
U.S. Pat. No. 5,503,161: Universal Medical Instrument Based on Spectrum Analysis, filed Oct. 25, 1993 and issued Apr. 2, 1996, shows how spectrum analysisxe2x80x94of light, sound and chemicalsxe2x80x94can play a key role in devising a universal instrument for medicine, and how this instrument""s general usefulness in medicine could be compared to that of the oscilloscope in electronics. In order to fully appreciate the timeliness of this patent, it is advisable not to skip the section entitled xe2x80x9cBackground of the Invention.xe2x80x9d The citations cover a range of social and technical requirements. It promotes a paradigm where resources are concentrated on the practitioner at the bedside. This patent was written after the author had actually built a working version of his neural network and demonstrated that it actually works for real-time frequency spectrum analysis. By now the neural engine was variously referred to as a xe2x80x9cresonant processor,xe2x80x9d a biocomputerxe2x80x9d or an xe2x80x9cartificial cochleaxe2x80x9d when programmed to work like the inner ear.
The apparatus of the Claims that follow is the same as that used in the neural engine of the previously referenced patents by the same author, but with further modifications and/or additions. All versions make it possible to realize a neural network with neurons that are capable of storing a multivalued quantity, said multivalued quantity also being able to grow or decay as a function of time.
In a first aspect, whereas the previous patents did describe a general methodology for performing frequency spectrum analysis, the present invention provides a number of additional hardware and software enabling details.
In a second aspect, whereas the previous versions used two multipliers and one adder to perform arithmetic, the present invention replaces one of the multipliers with a Coincidence Detector (3), thus significantly expanding the scope and capabilities of the neural recognition engine in areas other than frequency spectrum analysis.